Learning sparse quantum states from single-qubit measurements
quant-ph, cs.DS, cs.IT, math.IT
Submitted: 2026-09-28
Updated: 2026-09-28
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Quantum-Centric Algorithm for Sample-Based Krylov Diagonalization
- Quantum-centric simulation of hydrogen abstraction by sample-based quantum diagonalization and entanglement forging
- Observation of Improved Accuracy over Classical Sparse Ground-State Solvers using a Quantum Computer
- Quantum chemistry with provable convergence via randomized sample-based Krylov quantum diagonalization
- Learning State Preparation Circuits for Quantum Phases of Matter
- Efficient Direct Tomography for Matrix Product States
- Efficient Matrix Product State Learning in Logarithmic Depth
- Constant-Depth Quantum Imaginary Time Evolution Using Dynamic Fan-out Circuits
- Learning Mid-circuit Measurement Backaction from Three Repeated Measurements
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